Modeling of a Novel Tubular Double-Sided Switched Reluctance Linear Motor

Hao Chen, Jinfu Liu, Xing Wang, Popov Stanislav Olegovich, Evgeny A. Bodrenkov, Nurkhat Zhakiyev, Ton Duc

2025

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DOI 10.1109/tps.2025.3589076
Data confidence 85 high
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Abstract

This article presents a novel tubular double-sided switched reluctance linear motor (TDSRLM), and its magnetic characteristic is modeled. This article compares two modeling methods: magnetic equivalent circuit (MEC) and radial basis function (RBF) neural network. A 3-D finite element model (FEM) of TDSRLM is established to evaluate the accuracy of the model. The calculation results show that the MEC method can achieve relatively high accuracy when the motor is unsaturated. When the electromagnetic characteristic is nonlinear, the accuracy of MEC reduces significantly. The RBF neural network performs accurately when the motor is operated in nonlinear conditions.